Temporal evolution of α and β bands during visual spatial attention

Marrufo, Manuel Vázquez; Vaquero, Encarna; Cardoso, Marı́a Jesús; Gómez, Carlos

doi:10.1016/s0926-6410(01)00025-8

Cited by 121 publications

(70 citation statements)

References 20 publications

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“…Furthermore, research has shown that requiring individuals to divide their attention between two tasks results in a concomitant decrease in beta activity (Kristeva-Feige, Fritsch, Timmer, & Lucking, 2002). These findings are consistent with the suggestion that beta activity may represent a psychophysiological correlate of attentional processing (Vazquez-Marrufo, Vaquero, Cardoso, & Gomez, 2001). Therefore, the low levels of beta produced by children with ADHD are thought to have a detrimental effect on their ability to focus and concentrate.…”

Section: Journal Of Neurotherapysupporting

confidence: 82%

Neurofeedback as a Treatment for ADHD: A Methodological Review with Implications for Future Research

Вернон¹,

Frick²,

Gruzelier³

2004

Journal of Neurotherapy

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Section: Journal Of Neurotherapysupporting

confidence: 82%

Neurofeedback as a Treatment for ADHD: A Methodological Review with Implications for Future Research

Вернон¹,

Frick²,

Gruzelier³

2004

Journal of Neurotherapy

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“…Time evolution of the signals seems to play a significant role in visual attention tasks. Evidence from different studies [7,[14][15][16][17][18][19] seems to identify temporal aspects in visual attention mechanisms. In particular, two temporal phases are generally highlighted in these works: shift and sustained attention phases.…”

Section: Discussionmentioning

confidence: 99%

“…Secondly, we focused on the evolution of the features over time. Splitting the attention period into consecutive, non-overlapping, windows (of 150 ms [14]) allowed us to perform a time-dependent feature selection and classification. In particular, the selected window length ensured at least one complete oscillation of each analyzed frequency, i.e.…”

Section: The Four Different Approachesmentioning

confidence: 99%

“…Secondly, we hypothesize that attention-related patterns are evolving over time and consequently a time-dependent approach would enhance BCI performances. Previous neurophysiological studies have already highlighted the role of temporal dynamics in attention mechanisms [7,[14][15][16][17][18][19]. However, these important aspects are not yet exploited in the current BCI systems.…”

Section: Introductionmentioning

confidence: 99%

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Time-dependent approach for single trial classification of covert visuospatial attention

Tonin¹,

Leeb²,

Millán³

2012

J. Neural Eng.

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Recently, several studies have started to explore covert visuospatial attention as a control signal for brain-computer interfaces (BCIs). Covert visuospatial attention represents the ability to change the focus of attention from one point in the space without overt eye movements. Nevertheless, the full potential and possible applications of this paradigm remain relatively unexplored. Voluntary covert visuospatial attention might allow a more natural and intuitive interaction with real environments as neither stimulation nor gazing is required. In order to identify brain correlates of covert visuospatial attention, classical approaches usually rely on the whole α-band over long time intervals. In this work, we propose a more detailed analysis in the frequency and time domains to enhance classification performance. In particular, we investigate the contribution of α sub-bands and the role of time intervals in carrying information about visual attention. Previous neurophysiological studies have already highlighted the role of temporal dynamics in attention mechanisms. However, these important aspects are not yet exploited in BCI. In this work, we studied different methods that explicitly cope with the natural brain dynamics during visuospatial attention tasks in order to enhance BCI robustness and classification performances. Results with ten healthy subjects demonstrate that our approach identifies spectro-temporal patterns that outperform the state-of-the-art classification method. On average, our time-dependent classification reaches 0.74 ± 0.03 of the area under the ROC (receiver operating characteristic) curve (AUC) value with an increase of 12.3% with respect to standard methods (0.65 ± 0.4). In addition, the proposed approach allows faster classification (<1 instead of 3 s), without compromising performances. Finally, our analysis highlights the fact that discriminant patterns are not stable for the whole trial period but are changing over short time intervals. These results support the hypothesis that visual attention information is actually indexed by subject-specific α sub-bands and is time dependent.

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“…Beta activity has often been associated with states of high alertness, concentration and focused attention (e.g. Gomez et al, 1998;Vazquez Marrufo et al, 2001;Kristeva-Feige et al, 2002). The low levels of beta produced by children with ADHD (Clarke et al, 1998(Clarke et al, , 2001Monastra et al, 1999) are thought to have a detrimental effect on their ability to focus and concentrate.…”

Section: Introductionmentioning

confidence: 99%

Validating the efficacy of neurofeedback for optimising performance

Gruzelier

Egner

Вернон

2006

Progress in Brain Research

139

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Abstract:The field of neurofeedback training has largely proceeded without validation.Here we review our studies directed at validating SMR, beta and alpha-theta protocols for improving attention, memory, mood and music and dance performance in healthy participants. Important benefits were demonstrable with cognitive and neurophysiological measures which were predicted on the basis of regression models of learning. These are initial steps in providing a much needed scientific basis to neurofeedback, but much remains to be done.

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Temporal evolution of α and β bands during visual spatial attention

Cited by 121 publications

References 20 publications

Neurofeedback as a Treatment for ADHD: A Methodological Review with Implications for Future Research

Neurofeedback as a Treatment for ADHD: A Methodological Review with Implications for Future Research

Time-dependent approach for single trial classification of covert visuospatial attention

Validating the efficacy of neurofeedback for optimising performance

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